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This paper is in the following e-collection/theme issue:

Formative Evaluation of Digital Health Interventions (4896) Extended Reality, Virtual Reality and Virtual Worlds (1093) Participatory Medicine & E-Patients (977) Consumer & Patient Education and Shared-Decision Making (1241) User Needs and Competencies (569) E-Health / Health Services Research and New Models of Care (1144) Shared Decision Making and Self-Advocacy (87)

Published on in Vol 9 (2025)

This is a member publication of University of Strathclyde (Jisc)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/65235, first published .
Detailed 3D anatomical model of human skeleton, arteries, and veins.

Patient and Public Perceptions of 3D Technologies (Models and Images) to Facilitate Health Care Consultations: Exploratory, Mixed Methods Study

Patient and Public Perceptions of 3D Technologies (Models and Images) to Facilitate Health Care Consultations: Exploratory, Mixed Methods Study

Authors of this article:

Harleen Kaur Rai1 Author Orcid Image ;   Morven Miller1 Author Orcid Image ;   Steve Leung2 Author Orcid Image ;   Euan Macleod3 Author Orcid Image ;   Marilyn Lennon1 Author Orcid Image
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  1. Buser M, de Boer S, Häntze H, Muselaers S, Fütterer J, Busch F, Sountoulides P, Stanzione A, Bressem K, Adams L, Smit E, Prokop M, Hering A. Deep learning–based clinical decision support for renal cell carcinoma using computed tomography: An expert-informed scoping review. European Journal of Radiology Artificial Intelligence 2026;7:100110 View